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An Ensemble Quadratic Echo State Network for Nonlinear Spatio-Temporal Forecasting
Spatio-temporal data and processes are prevalent across a wide variety of scientific disciplines. These processes are often characterized by nonlinear time dynamics that include interactions across multiple scales of spatial and temporal variability. The data sets associated with many of these processes are increasin...
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Profit Maximization for Online Advertising Demand-Side Platforms
We develop an optimization model and corresponding algorithm for the management of a demand-side platform (DSP), whereby the DSP aims to maximize its own profit while acquiring valuable impressions for its advertiser clients. We formulate the problem of profit maximization for a DSP interacting with ad exchanges in a...
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Traces of surfactants can severely limit the drag reduction of superhydrophobic surfaces
Superhydrophobic surfaces (SHSs) have the potential to achieve large drag reduction for internal and external flow applications. However, experiments have shown inconsistent results, with many studies reporting significantly reduced performance. Recently, it has been proposed that surfactants, ubiquitous in flow appl...
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Non-Convex Rank/Sparsity Regularization and Local Minima
This paper considers the problem of recovering either a low rank matrix or a sparse vector from observations of linear combinations of the vector or matrix elements. Recent methods replace the non-convex regularization with $\ell_1$ or nuclear norm relaxations. It is well known that this approach can be guaranteed to...
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Supervised Speech Separation Based on Deep Learning: An Overview
Speech separation is the task of separating target speech from background interference. Traditionally, speech separation is studied as a signal processing problem. A more recent approach formulates speech separation as a supervised learning problem, where the discriminative patterns of speech, speakers, and backgroun...
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Sample Efficient Feature Selection for Factored MDPs
In reinforcement learning, the state of the real world is often represented by feature vectors. However, not all of the features may be pertinent for solving the current task. We propose Feature Selection Explore and Exploit (FS-EE), an algorithm that automatically selects the necessary features while learning a Fact...
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Sgoldstino-less inflation and low energy SUSY breaking
We assess the range of validity of sgoldstino-less inflation in a scenario of low energy supersymmetry breaking. We first analyze the consistency conditions that an effective theory of the inflaton and goldstino superfields should satisfy in order to be faithfully described by a sgoldstino-less model. Enlarging the s...
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SideEye: A Generative Neural Network Based Simulator of Human Peripheral Vision
Foveal vision makes up less than 1% of the visual field. The other 99% is peripheral vision. Precisely what human beings see in the periphery is both obvious and mysterious in that we see it with our own eyes but can't visualize what we see, except in controlled lab experiments. Degradation of information in the peri...
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Carbon stars in the X-Shooter Spectral Library: II. Comparison with models
In a previous paper, we assembled a collection of medium-resolution spectra of 35 carbon stars, covering optical and near-infrared wavelengths from 400 to 2400 nm. The sample includes stars from the Milky Way and the Magellanic Clouds, with a variety of $(J-K_s)$ colors and pulsation properties. In the present paper,...
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Four-variable expanders over the prime fields
Let $\mathbb{F}_p$ be a prime field of order $p>2$, and $A$ be a set in $\mathbb{F}_p$ with very small size in terms of $p$. In this note, we show that the number of distinct cubic distances determined by points in $A\times A$ satisfies \[|(A-A)^3+(A-A)^3|\gg |A|^{8/7},\] which improves a result due to Yazici, Murphy...
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Limit multiplicities for ${\rm SL}_2(\mathcal{O}_F)$ in ${\rm SL}_2(\mathbb{R}^{r_1}\oplus\mathbb{C}^{r_2})$
We prove that the family of lattices ${\rm SL}_2(\mathcal{O}_F)$, $F$ running over number fields with fixed archimedean signature $(r_1, r_2)$, in ${\rm SL}_2(\mathbb{R}^{r_1}\oplus\mathbb{C}^{r_2})$ has the limit multiplicity property.
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On comparing clusterings: an element-centric framework unifies overlaps and hierarchy
Clustering is one of the most universal approaches for understanding complex data. A pivotal aspect of clustering analysis is quantitatively comparing clusterings; clustering comparison is the basis for tasks such as clustering evaluation, consensus clustering, and tracking the temporal evolution of clusters. For exa...
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Parametric Oscillatory Instability in a Fabry-Perot Cavity of the Einstein Telescope with different mirror's materials
We discuss the parametric oscillatory instability in a Fabry-Perot cavity of the Einstein Telescope. Unstable combinations of elastic and optical modes for two possible configurations of gravitational wave third-generation detector are deduced. The results are compared with the results for gravita- tional wave interf...
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Mapping properties of the Hilbert and Fubini--Study maps in Kähler geometry
Suppose that we have a compact Kähler manifold $X$ with a very ample line bundle $\mathcal{L}$. We prove that any positive definite hermitian form on the space $H^0 (X,\mathcal{L})$ of holomorphic sections can be written as an $L^2$-inner product with respect to an appropriate hermitian metric on $\mathcal{L}$. We ap...
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Space-time Constructivism vs. Modal Provincialism: Or, How Special Relativistic Theories Needn't Show Minkowski Chronogeometry
In 1835 Lobachevski entertained the possibility of multiple (rival) geometries. This idea has reappeared on occasion (e.g., Poincaré) but didn't become key in space-time foundations prior to Brown's \emph{Physical Relativity} (at the end, the interpretive key to the book). A crucial difference between his constructiv...
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On the representation of integers by binary quadratic forms
In this note we show that for a given irreducible binary quadratic form $f(x,y)$ with integer coefficients, whenever we have $f(x,y) = f(u,v)$ for integers $x,y,u,v$, there exists a rational automorphism of $f$ which sends $(x,y)$ to $(u,v)$.
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The First Planetary Microlensing Event with Two Microlensed Source Stars
We present the analysis of microlensing event MOA-2010-BLG-117, and show that the light curve can only be explained by the gravitational lensing of a binary source star system by a star with a Jupiter mass ratio planet. It was necessary to modify standard microlensing modeling methods to find the correct light curve ...
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A Learning-Based Approach for Lane Departure Warning Systems with a Personalized Driver Model
Misunderstanding of driver correction behaviors (DCB) is the primary reason for false warnings of lane-departure-prediction systems. We propose a learning-based approach to predicting unintended lane-departure behaviors (LDB) and the chance for drivers to bring the vehicle back to the lane. First, in this approach, a...
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Internet of Things: Survey on Security and Privacy
The Internet of Things (IoT) is intended for ubiquitous connectivity among different entities or "things". While its purpose is to provide effective and efficient solutions, security of the devices and network is a challenging issue. The number of devices connected along with the ad-hoc nature of the system further e...
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A Connectedness Constraint for Learning Sparse Graphs
Graphs are naturally sparse objects that are used to study many problems involving networks, for example, distributed learning and graph signal processing. In some cases, the graph is not given, but must be learned from the problem and available data. Often it is desirable to learn sparse graphs. However, making a gr...
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Quotients of finite-dimensional operators by symmetry representations
A finite dimensional operator that commutes with some symmetry group admits quotient operators, which are determined by the choice of associated representation. Taking the quotient isolates the part of the spectrum supporting the chosen representation and reduces the complexity of the problem, however it is not uniqu...
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A probabilistic framework for the control of systems with discrete states and stochastic excitation
A probabilistic framework is proposed for the optimization of efficient switched control strategies for physical systems dominated by stochastic excitation. In this framework, the equation for the state trajectory is replaced with an equivalent equation for its probability distribution function in the constrained opt...
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Supersonic Flow onto Solid Wedges, Multidimensional Shock Waves and Free Boundary Problems
When an upstream steady uniform supersonic flow impinges onto a symmetric straight-sided wedge, governed by the Euler equations, there are two possible steady oblique shock configurations if the wedge angle is less than the detachment angle -- the steady weak shock with supersonic or subsonic downstream flow (determi...
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A Zero-Shot Learning application in Deep Drawing process using Hyper-Process Model
One of the consequences of passing from mass production to mass customization paradigm in the nowadays industrialized world is the need to increase flexibility and responsiveness of manufacturing companies. The high-mix / low-volume production forces constant accommodations of unknown product variants, which ultimate...
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Fracton topological phases from strongly coupled spin chains
We provide a new perspective on fracton topological phases, a class of three-dimensional topologically ordered phases with unconventional fractionalized excitations that are either completely immobile or only mobile along particular lines or planes. We demonstrate that a wide range of these fracton phases can be cons...
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The Internet as Quantitative Social Science Platform: Insights from a Trillion Observations
With the large-scale penetration of the internet, for the first time, humanity has become linked by a single, open, communications platform. Harnessing this fact, we report insights arising from a unified internet activity and location dataset of an unparalleled scope and accuracy drawn from over a trillion (1.5$\tim...
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Deep Embedding Kernel
In this paper, we propose a novel supervised learning method that is called Deep Embedding Kernel (DEK). DEK combines the advantages of deep learning and kernel methods in a unified framework. More specifically, DEK is a learnable kernel represented by a newly designed deep architecture. Compared with pre-defined ker...
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A Radio-Inertial Localization and Tracking System with BLE Beacons Prior Maps
In this paper, we develop a system for the low-cost indoor localization and tracking problem using radio signal strength indicator, Inertial Measurement Unit (IMU), and magnetometer sensors. We develop a novel and simplified probabilistic IMU motion model as the proposal distribution of the sequential Monte-Carlo tec...
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Simple groups, generation and probabilistic methods
It is well known that every finite simple group can be generated by two elements and this leads to a wide range of problems that have been the focus of intensive research in recent years. In this survey article we discuss some of the extraordinary generation properties of simple groups, focussing on topics such as ra...
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Large polaron evolution in anatase TiO2 due to carrier and temperature dependence of electron-phonon coupling
The electronic and magneto transport properties of reduced anatase TiO2 epitaxial thin films are analyzed considering various polaronic effects. Unexpectedly, with increasing carrier concentration, the mobility increases, which rarely happens in common metallic systems. We find that the screening of the electron-phon...
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AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks
New types of machine learning hardware in development and entering the market hold the promise of revolutionizing deep learning in a manner as profound as GPUs. However, existing software frameworks and training algorithms for deep learning have yet to evolve to fully leverage the capability of the new wave of silico...
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Random data wave equations
Nowadays we have many methods allowing to exploit the regularising properties of the linear part of a nonlinear dispersive equation (such as the KdV equation, the nonlinear wave or the nonlinear Schroedinger equations) in order to prove well-posedness in low regularity Sobolev spaces. By well-posedness in low regular...
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The Persistent Homotopy Type Distance
We introduce the persistent homotopy type distance dHT to compare real valued functions defined on possibly different homotopy equivalent topological spaces. The underlying idea in the definition of dHT is to measure the minimal shift that is necessary to apply to one of the two functions in order that the sublevel s...
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Optimal algorithms for smooth and strongly convex distributed optimization in networks
In this paper, we determine the optimal convergence rates for strongly convex and smooth distributed optimization in two settings: centralized and decentralized communications over a network. For centralized (i.e. master/slave) algorithms, we show that distributing Nesterov's accelerated gradient descent is optimal a...
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Superconductivity in ultra-thin carbon nanotubes and carbyne-nanotube composites: an ab-initio approach
The superconductivity of the 4-angstrom single-walled carbon nanotubes (SWCNTs) was discovered more than a decade ago, and marked the breakthrough of finding superconductivity in pure elemental undoped carbon compounds. The van Hove singularities in the electronic density of states at the Fermi level in combination w...
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Exponential lower bounds for history-based simplex pivot rules on abstract cubes
The behavior of the simplex algorithm is a widely studied subject. Specifically, the question of the existence of a polynomial pivot rule for the simplex algorithm is of major importance. Here, we give exponential lower bounds for three history-based pivot rules. Those rules decide their next step based on memory of ...
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Machine learning regression on hyperspectral data to estimate multiple water parameters
In this paper, we present a regression framework involving several machine learning models to estimate water parameters based on hyperspectral data. Measurements from a multi-sensor field campaign, conducted on the River Elbe, Germany, represent the benchmark dataset. It contains hyperspectral data and the five water...
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Critical factors and enablers of food quality and safety compliance risk management in the Vietnamese seafood supply chain
Recently, along with the emergence of food scandals, food supply chains have to face with ever-increasing pressure from compliance with food quality and safety regulations and standards. This paper aims to explore critical factors of compliance risk in food supply chain with an illustrated case in Vietnamese seafood ...
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Asymptotic behavior of semilinear parabolic equations on the circle with time almost-periodic/recurrent dependence
We study topological structure of the $\omega$-limit sets of the skew-product semiflow generated by the following scalar reaction-diffusion equation \begin{equation*} u_{t}=u_{xx}+f(t,u,u_{x}),\,\,t>0,\,x\in S^{1}=\mathbb{R}/2\pi \mathbb{Z}, \end{equation*} where $f(t,u,u_x)$ is $C^2$-admissible with time-recurrent s...
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Exploring 4D Quantum Hall Physics with a 2D Topological Charge Pump
The discovery of topological states of matter has profoundly augmented our understanding of phase transitions in physical systems. Instead of local order parameters, topological phases are described by global topological invariants and are therefore robust against perturbations. A prominent example thereof is the two...
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Non-hermitian operator modelling of basic cancer cell dynamics
We propose a dynamical system of tumor cells proliferation based on operatorial methods. The approach we propose is quantum-like: we use ladder and number operators to describe healthy and tumor cells birth and death, and the evolution is ruled by a non-hermitian Hamiltonian which includes, in a non reversible way, t...
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Giant ripples on comet 67P/Churyumov-Gerasimenko sculpted by sunset thermal wind
Explaining the unexpected presence of dune-like patterns at the surface of the comet 67P/Churyumov-Gerasimenko requires conceptual and quantitative advances in the understanding of surface and outgassing processes. We show here that vapor flow emitted by the comet around its perihelion spreads laterally in a surface ...
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A ROS multi-ontology references services: OWL reasoners and application prototyping issues
The challenge of sharing and communicating information is crucial in complex human-robot interaction (HRI) scenarios. Ontologies and symbolic reasoning are the state-of-the-art approaches for a natural representation of knowledge, especially within the Semantic Web domain. In such a context, scripted paradigms have b...
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Efficient Covariance Approximations for Large Sparse Precision Matrices
The use of sparse precision (inverse covariance) matrices has become popular because they allow for efficient algorithms for joint inference in high-dimensional models. Many applications require the computation of certain elements of the covariance matrix, such as the marginal variances, which may be non-trivial to o...
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The Density of Numbers Represented by Diagonal Forms of Large Degree
Let $s \geq 3$ be a fixed positive integer and $a_1,\dots,a_s \in \mathbb{Z}$ be arbitrary. We show that, on average over $k$, the density of numbers represented by the degree $k$ diagonal form \[ a_1 x_1^k + \cdots + a_s x_s^k \] decays rapidly with respect to $k$.
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Meta-Learning for Resampling Recommendation Systems
One possible approach to tackle the class imbalance in classification tasks is to resample a training dataset, i.e., to drop some of its elements or to synthesize new ones. There exist several widely-used resampling methods. Recent research showed that the choice of resampling method significantly affects the quality...
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Robustness Analysis of Systems' Safety through a New Notion of Input-to-State Safety
In this paper, we propose a new robustness notion that is applicable for certifying systems' safety with respect to external disturbance signals. The proposed input-to-state safety (ISSf) notion allows us to certify systems' safety in the presence of the disturbances which is analogous to the notion of input-to-state...
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Estimating ground-level PM2.5 by fusing satellite and station observations: A geo-intelligent deep learning approach
Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geograph...
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An Overview of Recent Progress in Laser Wakefield Acceleration Experiments
The goal of this paper is to examine experimental progress in laser wakefield acceleration over the past decade (2004-2014), and to use trends in the data to understand some of the important physical processes. By examining a set of over 50 experiments, various trends concerning the relationship between plasma densit...
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MindID: Person Identification from Brain Waves through Attention-based Recurrent Neural Network
Person identification technology recognizes individuals by exploiting their unique, measurable physiological and behavioral characteristics. However, the state-of-the-art person identification systems have been shown to be vulnerable, e.g., contact lenses can trick iris recognition and fingerprint films can deceive f...
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Beyond black-boxes in Bayesian inverse problems and model validation: applications in solid mechanics of elastography
The present paper is motivated by one of the most fundamental challenges in inverse problems, that of quantifying model discrepancies and errors. While significant strides have been made in calibrating model parameters, the overwhelming majority of pertinent methods is based on the assumption of a perfect model. Moti...
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On the Spectral Properties of Symmetric Functions
We characterize the approximate monomial complexity, sign monomial complexity , and the approximate L 1 norm of symmetric functions in terms of simple combinatorial measures of the functions. Our characterization of the approximate L 1 norm solves the main conjecture in [AFH12]. As an application of the characterizat...
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Strong light shifts from near-resonant and polychromatic fields: comparison of Floquet theory and experiment
We present a non-perturbative numerical technique for calculating strong light shifts in atoms under the influence of multiple optical fields with arbitrary polarization. We confirm our technique experimentally by performing spectroscopy of a cloud of cold $^{87}$Rb atoms subjected to $\sim$ kW/cm$^2$ intensities of ...
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Positive-rank elliptic curves arising pythagorean triples
In the present paper, we introduce some new families of elliptic curves with positive rank arrising from Pythagorean triples.
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Modeling Relational Data with Graph Convolutional Networks
Knowledge graphs enable a wide variety of applications, including question answering and information retrieval. Despite the great effort invested in their creation and maintenance, even the largest (e.g., Yago, DBPedia or Wikidata) remain incomplete. We introduce Relational Graph Convolutional Networks (R-GCNs) and a...
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Application of shifted-Laplace preconditioners for heterogenous Helmholtz equation- part 1: Data modelling
In several geophysical applications, such as full waveform inversion and data modelling, we are facing the solution of inhomogeneous Helmholtz equation. The difficulties of solving the Helmholtz equa- tion are two fold. Firstly, in the case of large scale problems we cannot calculate the inverse of the Helmholtz oper...
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Algorithms For Longest Chains In Pseudo- Transitive Graphs
A directed acyclic graph G = (V, E) is pseudo-transitive with respect to a given subset of edges E1, if for any edge ab in E1 and any edge bc in E, we have ac in E. We give algorithms for computing longest chains and demonstrate geometric applications that unify and improves some important past results. (For specific...
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From time-series to complex networks: Application to the cerebrovascular flow patterns in atrial fibrillation
A network-based approach is presented to investigate the cerebrovascular flow patterns during atrial fibrillation (AF) with respect to normal sinus rhythm (NSR). AF, the most common cardiac arrhythmia with faster and irregular beating, has been recently and independently associated with the increased risk of dementia...
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On the matrix $pth$ root functions and generalized Fibonacci sequences
This study is devoted to the polynomial representation of the matrix $p$th root functions. The Fibonacci-Hörner decomposition of the matrix powers and some techniques arisen from properties of generalized Fibonacci sequences, notably the Binet formula, serves as a triggering factor to provide explicit formulas for th...
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Investigation and Automating Extraction of Thumbnails Produced by Image viewers
Today, in digital forensics, images normally provide important information within an investigation. However, not all images may still be available within a forensic digital investigation as they were all deleted for example. Data carving can be used in this case to retrieve deleted images but the carving time is norm...
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Weighted network estimation by the use of topological graph metrics
Topological metrics of graphs provide a natural way to describe the prominent features of various types of networks. Graph metrics describe the structure and interplay of graph edges and have found applications in many scientific fields. In this work, graph metrics are used in network estimation by developing optimis...
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Petrophysical property estimation from seismic data using recurrent neural networks
Reservoir characterization involves the estimation petrophysical properties from well-log data and seismic data. Estimating such properties is a challenging task due to the non-linearity and heterogeneity of the subsurface. Various attempts have been made to estimate petrophysical properties using machine learning te...
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Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading
Deep learning applies hierarchical layers of hidden variables to construct nonlinear high dimensional predictors. Our goal is to develop and train deep learning architectures for spatio-temporal modeling. Training a deep architecture is achieved by stochastic gradient descent (SGD) and drop-out (DO) for parameter reg...
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Multi-objective Bandits: Optimizing the Generalized Gini Index
We study the multi-armed bandit (MAB) problem where the agent receives a vectorial feedback that encodes many possibly competing objectives to be optimized. The goal of the agent is to find a policy, which can optimize these objectives simultaneously in a fair way. This multi-objective online optimization problem is ...
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Floquet multi-Weyl points in crossing-nodal-line semimetals
Weyl points with monopole charge $\pm 1$ have been extensively studied, however, real materials of multi-Weyl points, whose monopole charges are higher than $1$, have yet to be found. In this Rapid Communication, we show that nodal-line semimetals with nontrivial line connectivity provide natural platforms for realiz...
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Impact Ionization in $β-Ga_2O_3$
A theoretical investigation of extremely high field transport in an emerging wide-bandgap material $\beta-Ga_2O_3$ is reported from first principles. The signature high-field effect explored here is impact ionization. Interaction between a valence-band electron and an excited electron is computed from the matrix elem...
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Entombed: An archaeological examination of an Atari 2600 game
The act and experience of programming is, at its heart, a fundamentally human activity that results in the production of artifacts. When considering programming, therefore, it would be a glaring omission to not involve people who specialize in studying artifacts and the human activity that yields them: archaeologists...
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Particle Filters for Partially-Observed Boolean Dynamical Systems
Partially-observed Boolean dynamical systems (POBDS) are a general class of nonlinear models with application in estimation and control of Boolean processes based on noisy and incomplete measurements. The optimal minimum mean square error (MMSE) algorithms for POBDS state estimation, namely, the Boolean Kalman filter...
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Cross-National Measurement of Polarization in Political Discourse: Analyzing floor debate in the U.S. and the Japanese legislatures
Political polarization in public space can seriously hamper the function and the integrity of contemporary democratic societies. In this paper, we propose a novel measure of such polarization, which, by way of simple topic modelling, quantifies differences in collective articulation of public agendas among relevant p...
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Size-Change Termination as a Contract
Program termination is an undecidable, yet important, property relevant to program verification, optimization, debugging, partial evaluation, and dependently-typed programming, among many other topics. This has given rise to a large body of work on static methods for conservatively predicting or enforcing termination...
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Disorder Dependent Valley Properties in Monolayer WSe2
We investigate the effect on disorder potential on exciton valley polarization and valley coherence in monolayer WSe2. By analyzing polarization properties of photoluminescence, the valley coherence (VC) and valley polarization (VP) is quantified across the inhomogeneously broadened exciton resonance. We find that di...
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Results on the Hilbert coefficients and reduction numbers
Let $(R,\frak{m})$ be a $d$-dimensional Cohen-Macaulay local ring, $I$ an $\frak{m}$-primary ideal and $J$ a minimal reduction of $I$. In this paper we study the independence of reduction ideals and the behavior of the higher Hilbert coefficients. In addition, we give some examples in this regards.
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Progress on Experiments towards LWFA-driven Transverse Gradient Undulator-Based FELs
Free Electron Lasers (FEL) are commonly regarded as the potential key application of laser wakefield accelerators (LWFA). It has been found that electron bunches exiting from state-of-the-art LWFAs exhibit a normalized 6-dimensional beam brightness comparable to those in conventional linear accelerators. Effectively ...
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Non-escaping endpoints do not explode
The family of exponential maps $f_a(z)= e^z+a$ is of fundamental importance in the study of transcendental dynamics. Here we consider the topological structure of certain subsets of the Julia set $J(f_a)$. When $a\in (-\infty,-1)$, and more generally when $a$ belongs to the Fatou set of $f_a$, it is known that $J(f_a...
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The Fornax Deep Survey with VST. II. Fornax A: a two-phase assembly caught on act
As part of the Fornax Deep Survey with the ESO VLT Survey Telescope, we present new $g$ and $r$ bands mosaics of the SW group of the Fornax cluster. It covers an area of $3 \times 2$ square degrees around the central galaxy NGC1316. The deep photometry, the high spatial resolution of OmegaCam and the large covered ar...
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Local decoding and testing of polynomials over grids
The well-known DeMillo-Lipton-Schwartz-Zippel lemma says that $n$-variate polynomials of total degree at most $d$ over grids, i.e. sets of the form $A_1 \times A_2 \times \cdots \times A_n$, form error-correcting codes (of distance at least $2^{-d}$ provided $\min_i\{|A_i|\}\geq 2$). In this work we explore their loc...
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A New Backpressure Algorithm for Joint Rate Control and Routing with Vanishing Utility Optimality Gaps and Finite Queue Lengths
The backpressure algorithm has been widely used as a distributed solution to the problem of joint rate control and routing in multi-hop data networks. By controlling a parameter $V$ in the algorithm, the backpressure algorithm can achieve an arbitrarily small utility optimality gap. However, this in turn brings in a ...
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Lifshitz transition from valence fluctuations in YbAl3
In Kondo lattice systems with mixed valence, such as YbAl3, interactions between localized electrons in a partially filled f shell and delocalized conduction electrons can lead to fluctuations between two different valence configurations with changing temperature or pressure. The impact of this change on the momentum...
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Diversity from the Topology of Citation Networks
We study transitivity in directed acyclic graphs and its usefulness in capturing nodes that act as bridges between more densely interconnected parts in such type of network. In transitively reduced citation networks degree centrality could be used as a measure of interdisciplinarity or diversity. We study the measure...
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Superluminal transmission of phase modulation information by a long macroscopic pulse propagating through interstellar space
A method of transmitting information in interstellar space at superluminal, or $> c$, speeds is proposed. The information is encoded as phase modulation of an electromagnetic wave of constant intensity, i.e. fluctuations in the rate of energy transport plays no role in the communication, and no energy is transported ...
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Causal Regularization
In application domains such as healthcare, we want accurate predictive models that are also causally interpretable. In pursuit of such models, we propose a causal regularizer to steer predictive models towards causally-interpretable solutions and theoretically study its properties. In a large-scale analysis of Electr...
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Voice Disorder Detection Using Long Short Term Memory (LSTM) Model
Automated detection of voice disorders with computational methods is a recent research area in the medical domain since it requires a rigorous endoscopy for the accurate diagnosis. Efficient screening methods are required for the diagnosis of voice disorders so as to provide timely medical facilities in minimal resou...
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Topology of two-dimensional turbulent flows of dust and gas
We perform direct numerical simulations (DNS) of passive heavy inertial particles (dust) in homogeneous and isotropic two-dimensional turbulent flows (gas) for a range of Stokes number, ${\rm St} < 1$, using both Lagrangian and Eulerian approach (with a shock-capturing scheme). We find that: The dust-density field in...
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Trimming the Independent Fat: Sufficient Statistics, Mutual Information, and Predictability from Effective Channel States
One of the most fundamental questions one can ask about a pair of random variables X and Y is the value of their mutual information. Unfortunately, this task is often stymied by the extremely large dimension of the variables. We might hope to replace each variable by a lower-dimensional representation that preserves ...
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Statistical Physics of the Symmetric Group
Ordered chains (such as chains of amino acids) are ubiquitous in biological cells, and these chains perform specific functions contingent on the sequence of their components. Using the existence and general properties of such sequences as a theoretical motivation, we study the statistical physics of systems whose sta...
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A New Phosphorus Allotrope with Direct Band Gap and High Mobility
Based on ab initio evolutionary crystal structure search computation, we report a new phase of phosphorus called green phosphorus ({\lambda}-P), which exhibits the direct band gaps ranging from 0.7 to 2.4 eV and the strong anisotropy in optical and transport properties. Free energy calculations show that a single-lay...
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An open shop approach in approximating optimal data transmission duration in WDM networks
In the past decade Optical WDM Networks (Wavelength Division Multiplexing) are being used quite often and especially as far as broadband applications are concerned. Message packets transmitted through such networks can be interrupted using time slots in order to maximize network usage and minimize the time required f...
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Optimal prediction in the linearly transformed spiked model
We consider the linearly transformed spiked model, where observations $Y_i$ are noisy linear transforms of unobserved signals of interest $X_i$: \begin{align*} Y_i = A_i X_i + \varepsilon_i, \end{align*} for $i=1,\ldots,n$. The transform matrices $A_i$ are also observed. We model $X_i$ as random vectors lying on an u...
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Self-Normalizing Neural Networks
Deep Learning has revolutionized vision via convolutional neural networks (CNNs) and natural language processing via recurrent neural networks (RNNs). However, success stories of Deep Learning with standard feed-forward neural networks (FNNs) are rare. FNNs that perform well are typically shallow and, therefore canno...
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Real-time Fault Localization in Power Grids With Convolutional Neural Networks
Diverse fault types, fast re-closures and complicated transient states after a fault event make real-time fault location in power grids challenging. Existing localization techniques in this area rely on simplistic assumptions, such as static loads, or require much higher sampling rates or total measurement availabili...
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Effective identifiability criteria for tensors and polynomials
A tensor $T$, in a given tensor space, is said to be $h$-identifiable if it admits a unique decomposition as a sum of $h$ rank one tensors. A criterion for $h$-identifiability is called effective if it is satisfied in a dense, open subset of the set of rank $h$ tensors. In this paper we give effective $h$-identifiabi...
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Functoriality properties of the dual group
Let $G$ be a connected reductive group. In a previous paper, arXiv:1702.08264, is was shown that the dual group $G^\vee_X$ attached to a $G$-variety $X$ admits a natural homomorphism with finite kernel to the Langlands dual group $G^\vee$ of $G$. Here, we prove that the dual group is functorial in the following sense...
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Chaotic dynamics around cometary nuclei
We apply a generalized Kepler map theory to describe the qualitative chaotic dynamics around cometary nuclei, based on accessible observational data for five comets whose nuclei are well-documented to resemble dumb-bells. The sizes of chaotic zones around the nuclei and the Lyapunov times of the motion inside these z...
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Riemannian curvature measures
A famous theorem of Weyl states that if $M$ is a compact submanifold of euclidean space, then the volumes of small tubes about $M$ are given by a polynomial in the radius $r$, with coefficients that are expressible as integrals of certain scalar invariants of the curvature tensor of $M$ with respect to the induced me...
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A new lower bound for the on-line coloring of intervals with bandwidth
The on-line interval coloring and its variants are important combinatorial problems with many applications in network multiplexing, resource allocation and job scheduling. In this paper we present a new lower bound of $4.1626$ for the competitive ratio for the on-line coloring of intervals with bandwidth which improv...
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Orbits of monomials and factorization into products of linear forms
This paper is devoted to the factorization of multivariate polynomials into products of linear forms, a problem which has applications to differential algebra, to the resolution of systems of polynomial equations and to Waring decomposition (i.e., decomposition in sums of d-th powers of linear forms; this problem is ...
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Monodromy and Vinberg fusion for the principal degeneration of the space of G-bundles
We study the geometry and the singularities of the principal direction of the Drinfeld-Lafforgue-Vinberg degeneration of the moduli space of G-bundles Bun_G for an arbitrary reductive group G, and their relationship to the Langlands dual group of G. In the first part of the article we study the monodromy action on th...
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Sketched Subspace Clustering
The immense amount of daily generated and communicated data presents unique challenges in their processing. Clustering, the grouping of data without the presence of ground-truth labels, is an important tool for drawing inferences from data. Subspace clustering (SC) is a relatively recent method that is able to succes...
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An infinite class of unsaturated rooted trees corresponding to designable RNA secondary structures
An RNA secondary structure is designable if there is an RNA sequence which can attain its maximum number of base pairs only by adopting that structure. The combinatorial RNA design problem, introduced by Haleš et al. in 2016, is to determine whether or not a given RNA secondary structure is designable. Haleš et al. i...
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Any Baumslag-Solitar action on surfaces with a pseudo-Anosov element has a finite orbit
We consider $f, h$ homeomorphims generating a faithful $BS(1,n)$-action on a closed surface $S$, that is, $h f h^{-1} = f^n$, for some $ n\geq 2$. According to \cite{GL}, after replacing $f$ by a suitable iterate if necessary, we can assume that there exists a minimal set $\Lambda$ of the action, included in $Fix(f)$...
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